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ICCV
2011
IEEE
12 years 8 months ago
HEAT: Iterative Relevance Feedback with One Million Images
It has been shown repeatedly that iterative relevance feedback is a very efficient solution for content-based image retrieval. However, no existing system scales gracefully to hu...
Nicolae Suditu, Francois Fleuret
ECCV
2004
Springer
14 years 10 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
MM
1996
ACM
538views Multimedia» more  MM 1996»
14 years 21 days ago
Comparing Images Using Color Coherence Vectors
Color histograms are used to compare images in many applications. Their advantages are efficiency, and insensitivity to small changes in camera viewpoint. However, color histogram...
Greg Pass, Ramin Zabih, Justin Miller
CVPR
2008
IEEE
14 years 10 months ago
Manifold learning using robust Graph Laplacian for interactive image search
Interactive image search or relevance feedback is the process which helps a user refining his query and finding difficult target categories. This consists in partially labeling a ...
Hichem Sahbi, Patrick Etyngier, Jean-Yves Audibert...
CVDB
2005
ACM
13 years 10 months ago
Optimizing progressive query-by-example over pre-clustered large image databases
The typical mode for querying in an image content-based information system is query-by-example, which allows the user to provide an image as a query and to search for similar imag...
Anicet Kouomou Choupo, Laure Berti-Equille, Annie ...